2026/2027 PhD Residency - Scientific ML (SciML) and Multiscale Physics (Early Stage Project)
How you will make 10x impact:
- Combining fluid dynamics and machine learning to solve some of the most important problems in materials discovery and manufacturing
- Working at the absolute forefront of simulation + experimentation, replacing computationally heavy, brute-force forward solvers with lean, physics-informed architectures
This project is focused on building advanced simulations and models along with custom equipment and processes to accelerate materials discovery and other critical manufacturing challenges.
- Location: X's headquarters in Mountain View, CA
- Start Date(s): Year-round rolling basis
- Duration: a flexible 6 mo. to 1 year program based on project team needs and your availability
Throughout your AI Residency you can expect:
- To be embedded into one of our confidential or public X projects
- To get paid competitively and receive benefits
- To be a part of a lively community of AI and ML Residents
- To attend tech-talks with AI leaders from across X
What you should have:
- Must be actively enrolled in a PhD program
- First-principles understanding of multiscale physics from continuous fluid dynamics to discrete particle modeling
- Proven expertise in Scientific Machine Learning (SciML), specifically the ability to parameterize unresolved or complex physics (e.g., phase coupling, closure terms) into autodifferentiable physics solvers and implement, optimize, and scale relevant SciML frameworks
- Practical familiarity with laboratory environments, physical instrumentation, or a strong, demonstrated inclination to tinker and build
It’d be great if you also had these:
- Direct experience with PINNs, Neural Operators, and traditional ML
- Proficiency in high-performance simulation tools (e.g., COMSOL, OpenFOAM)
- Track record of applying machine learning to complex physical systems (e.g., turbulence, multiphase flow, or inverse design)
Additional public information:
- https://www.wired.com/video/watch/astro-teller-captain-of-moonshots-at-x-speaks-at-wired25
- https://www.bloomberg.com/news/videos/2019-10-10/alphabet-x-s-astro-teller-on-bloomberg-studio-1-0-video
- https://www.npr.org/2025/09/12/nx-s1-5493348/astro-teller-takes-us-inside-the-moonshot-factory-building-tech-ahead-of-its-time
- https://time.com/collections/best-inventions-2024/7094574/x-taara/
- https://youtu.be/_iLJU4HORAA?si=aK8cHf64NUNcsZXr
- https://www.fastcompany.com/best-workplaces-for-innovators/list/84
The US base salary range for this position is $100,000 - $157,000 + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your location during the hiring process. Please note that the compensation details listed in US role postings reflect the base salary only, and do not include benefits.
Skills Required
- Must be actively enrolled in a PhD program
- First-principles understanding of multiscale physics, from continuous fluid dynamics to discrete particle modeling
- Proven expertise in Scientific Machine Learning, including parameterizing unresolved or complex physics into autodifferentiable physics solvers
- Ability to implement, optimize, and scale relevant Scientific Machine Learning frameworks
- Practical familiarity with laboratory environments or physical instrumentation, or a strong demonstrated inclination to tinker and build
- Direct experience with Physics-Informed Neural Networks (PINNs), Neural Operators, and traditional machine learning
- Proficiency in high-performance simulation tools such as COMSOL or OpenFOAM
- Track record of applying machine learning to complex physical systems, such as turbulence, multiphase flow, or inverse design
X, The Moonshot Factory Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about X, The Moonshot Factory and has not been reviewed or approved by X, The Moonshot Factory.
-
Fair & Transparent Compensation — Pay is considered competitive for core technical and senior roles, with employer-posted ranges and clear statements that total compensation includes base, bonus, equity, and benefits. Feedback suggests posted bands and explicit structure provide clarity on how pay is constructed.
-
Parental & Family Support — Family support is described as generous, including paid parental leave, baby bonding, and transitional support for parents returning to work. Fertility treatments and maternity care are also covered, indicating depth in family-focused provisions.
-
Retirement Support — Retirement programs include a 401(k) with a notable company match and immediate vesting of matched funds. Additional financial supports such as student loan reimbursement and coaching strengthen long-term financial security.
X, The Moonshot Factory Insights
What We Do
We create breakthrough technologies to help solve some of the world’s biggest problems. Born at Google, we got our start creating self-driving cars and smart glasses. Since then, we’ve continued to bring sci-fi ideas into reality.
